System for early detection of disease and development of disease-specific biomarkers

ABSTRACT

The present invention relates to a method for the detection of a specific disease in a mammal, comprising providing an NMR spectrum of metabolites in a body fluid of an individual of said mammal in which said disease is suspected and comparing said NMR spectrum with a difference profile, comprising a plurality of NMR spectral line positions, which express the normalized difference between one or more NMR spectra of metabolites in a body fluid of one or more healthy individuals of said mammal, and one or more corresponding NMR spectra of metabolites in a corresponding body fluid of one or more individuals of said mammal in which the disease has been diagnosed. The invention also relates to the said difference profile for the detection of a disease in a mammal and to methods for the manufacture thereof. The invention also relates to a biomarker for detection of specific diseases, in particular osteoarthritis, and to the use of that biomarker in detection of osteoarthritis.

The invention relates to a difference profile between NMR spectra ofmetabolic metabolites as a pattern for early detection of a disease in amammal, to a biomarker for detection of a disease, to a method formanufacturing a difference profile and to a method for theidentification of biomarkers by means of a difference profile. Finally,the present invention relates to a method for detection of a disease,especially osteoarthritis, in a mammal by means of a biomarker and/ordifference profile according to the invention.

In many cases, determining the health condition of an individual can bea difficult matter. Diagnosis is of course difficult if clinicalexamination reveals no cause of a health problem. Conversely, with somediseases, such as for instance cancer, an individual can have relativelyfew symptoms, but the disease can nevertheless be at an advanced stage.

For a large number of diseases, such as for instance MS andosteoarthritis, there is not even a diagnostic test (laboratorydetection or measurement technique) available at the moment by means ofwhich the disease can be diagnosed with 100% certainty. The diagnosis ofsuch diseases is complex and is often made on the basis of examinationof tissue functioning (e.g. nerves and joints respectively) incombination with biochemical and/or pathological tissue examination.This combination is important because, with this type of disorder,clinical examination may show a perfectly normal picture, while thepatient already has many symptoms. All the same, the medical specialistwill not always be able to diagnose the disease with certainty.Therefore, for an actual diagnosis, it is also necessary to demonstrateprogression of the clinical picture in time.

With the existing methods, the progression of the disease cannot bedetermined or cannot be simply determined. This makes it oftenimpossible to start a therapeutic treatment already at an early stage,so that the disease is often at an advanced stage even before medicationis administered.

Also, the absence of early diagnostics limits the development of morespecific and more effective therapies. There is a great need foralternative methods which can quantitatively, reliably, sensitively andspecifically demonstrate the presence of a disease. Further, there is aneed for a method by means of which particular diseases can be diagnosedat an early stage, preferably before the disease process has led toirreversible changes.

The use of molecular markers (or biomarkers) which are specific to thepresence of a particular disease could fill this need and can make animportant contribution to diagnosis, prognosis and monitoring of theprogress of the disease. Further, by means of such molecular markers,research into the effect of clinical treatment therapies and thedevelopment of new medicines could be facilitated. Thus, molecularmarkers are considered crucial for effectively carrying out preclinicalstudies (both in vitro and in vivo in laboratory animals) and studiesdirected at the pathophysiology of diseases in general.

An ideal molecular marker is disease-specific, reflects the actualdisease activity and/or disease stage, can be used for determining theeffectiveness of therapy and contributes to the reliable prognosis ofthe disease. However, all these requirements do not need to beintegrated in one single marker; a combination of complementary markersis possible and could, in particular cases, perform even better.

It is an object of the present invention to provide new systems andmethods for the detection of a disease.

Another object of the present invention is to provide systems andmethods which solve at least some of the problems associated withexisting systems and methods for the detection of a disease as describedhereinabove.

Another object of the present invention resides in providing systems andmethods as described hereinabove which can be used in in vivo and/or invitro medical diagnostics.

It has now been found that, in the urine of an individual with aparticular disease, such as for instance osteoarthritis, metabolites arepresent which are not, or in significantly larger or smaller quantities,present in healthy individuals. It was possible to demonstrate thepresence of these disease-specific metabolite concentrations by means ofa proton nuclear magnetic resonance (¹H NMR) spectroscopic analysis ofthe metabolites in the urine of mammals. Therefore, these metabolitescan be used, individually or in combination, as a biomarker in thediagnostics and prognostics of diseases.

It has further been found that a collection of statistically significantdifferences between the signal intensity of a large number of spectrallines with defined positions in the NMR spectrum, recorded frommetabolites in the urine of a healthy individual, and the signalintensity of corresponding spectral lines in the NMR spectrum recordedfrom metabolites in the urine of an individual suffering from a specificdisorder or disease can provide a pattern which enables the detection ofthat disease in that individual. In the present invention, this patternis referred to as a difference profile or metabolic fingerprint. Such adifference profile can be graphically represented as a factor spectrum(see FIGS. 1 and 2).

The present invention therefore relates to a difference profile for thedetection of a disease in a mammal, comprising a plurality of spectralline positions and, optionally, corresponding signal intensities of NMRspectral lines, which express the normalized difference between one ormore NMR spectra of metabolites in a body fluid of one or more healthyindividuals of this mammal, and one or more corresponding NMR spectra ofmetabolites in a corresponding body fluid of one or more individuals ofthis mammal in which the disease has already been diagnosed.

FIG. 1 is a representation of a score plot of NMR spectra obtained inthe manner as inter alia described in Example 1 for osteoarthritis. Onthe horizontal axis, component D1 is plotted. On the vertical axis,component D2 is plotted. The left outlined cluster (C) is a cluster ofNMR spectra of healthy control individuals, while the rightinterruptedly outlined cluster (OA) represents a cluster of NMR spectraof patients with osteoarthritis.

FIG. 2 is a representation of a factor spectrum of osteoarthritisobtained in the manner as described in the description below andExample 1. On the horizontal axis, the spectral line position is plottedin “ppm”. On the vertical axis, the signal intensity is plotted in“Regression”.

Osteoarthritis (cartilage degeneration) is one of the most commondiseases among elderly people and there is an incidence of more than 50%among people aged 65 years and over. Osteoarthritis is characterized byprogressive degradation of articular cartilage and results in impairedmovement, pain and ultimately disability. In addition to cartilagedegradation, osteoarthritis is pathologically characterized by changesin subchondral bone (sclerosis, cysts), osteophyte formation and mildsynovial inflammation. However, the etiology and pathogenesis ofosteoarthritis are largely unclear.

The clinical diagnosis of osteoarthritis is based on the observation ofclinical symptoms in combination with radiological examination ofchanges in the joint, especially related to the width of the jointspace. However, these changes can only be observed at an advanced stageof the disease. Often, the damage to the joints is already irreversibleby then. Since radiological determination of the width of the jointspace is relatively insensitive, moreover, after at least 1 year andpreferably 2 years, a follow-up examination is needed to determine theprogress of the disease and the possible effect of a therapy. Thisgreatly complicates the treatment of osteoarthritis.

Markers which are presently used in osteoarthritis-related examinationcomprise molecules such as COMP (cartilage oligomeric matrix protein),which, however, is not specific to cartilage, and Glc-Gal-PYD(glucosyl-galactosyl pyridinoline), which is a marker for thedegradation of synovial tissue (mucous lining) and can therefore notserve as a diagnostic marker of cartilage degradation. Another markerused is CTX-II, the C-terminal crosslinked telopeptide of type IIcollagen. This marker is collagen-specific. But since osteoarthritiscomprises more than just collagen-related components, use of this markercan yield false negative results.

There is a great need for alternative markers and/or methods which canquantitatively, reliably, sensitively and specifically demonstrateosteoarthritis-related changes in the joints. Further, there is a needfor a method by means of which osteoarthritis can be diagnosed at anearly stage, preferably before irreversible changes have taken place.

The present application now provides a method for the early detection ofa disease in a mammal, such as for instance osteoarthritis, by means ofa difference profile between NMR spectra of metabolic metabolites. Sucha method is preferably not invasive.

In the present invention, a difference profile is defined as acharacteristic selection of NMR spectral lines with defined positionswhose values of the signal intensities significantly differ betweennormalized NMR spectra of metabolites in a body fluid of ill patientsand normalized NMR spectra of metabolites in a body fluid of healthyindividuals. Such a difference profile comprises the spectral linepositions and optionally their corresponding signal intensities orsignal intensity differences.

In the present invention, a normalized NMR spectrum is defined as an NMRspectrum in which the diversity or variation in the signal intensitiesof the spectral lines between samples is limited by arithmeticallytaking glitches into account. For normalization, the sum of the squaresof all intensities is equated with 1. The reason for this is that it isassumed that each sample comprises an equal amount of information. Bycarrying out normalization, the absolute amount of information in eachNMR spectrum is equated (equal surfaces under the NMR spectra), so thatthey become mutually comparable.

A changing signal intensity of a particular spectral line in twocomparable NMR spectra indicates that the concentration of hydrogenatoms in one of those samples has changed and that, thus, the amount ofone or more chemical components containing these atoms, in this casemetabolites, has changed in one of those samples.

So, a difference profile according to the invention comprises acollection of spectral line positions in a normalized NMR spectrum whosecorresponding signal intensity is increased or decreased due to aspecific disease compared to the signal intensity in a normalized NMRspectrum of healthy individuals.

Preferably, a difference profile according to the invention comprisesspectral line positions whose corresponding signal intensities areincreased and/or decreased by a particular factor in the spectrum of anill patient in relation to a corresponding spectrum of a healthyindividual. This factor can be used for applying a (positive) thresholdvalue (or reference value) for increases and a corresponding (negative)threshold value for decreases of the signal intensity. Spectral linepositions whose corresponding signal intensities are above or below thecorresponding threshold value are included in the difference profile.The endogenous and exogenous metabolites (see below) whose signalintensity cannot be correlated to a healthy or to an ill situation havebeen eliminated from such a difference profile so that the data arereduced to specific and “significant” disease-related changes.

For eliminating endogenous and exogenous metabolites from a differenceprofile according to the invention, a threshold value which correspondsto approximately one and a half times, preferably approximately twotimes, more preferably approximately three times the signal to noiseratio can very suitably be used in the normalized spectrum. Here, noisein the NMR spectrum is understood to mean the signals coming fromaspecific measurement events, such as for instance machine noise,environmental fluctuations, and/or contaminations in the chemicals.

It is also possible to use the value of the average signal intensity of60-99%, preferably 70-95%, more preferably 80-90% of all spectral linepositions showing a change in intensity between healthy individuals andill individuals as a threshold value for obtaining difference profileaccording to the invention.

The choice for the level of the threshold value will also inter aliadepend on the individual properties of the mammal for which thedifference profile is determined. Such properties comprise sex, age,stage of life (fertile/infertile), diet, possible medication, geneticbackground, and, in humans, tobacco and/or alcohol consumption. The useof homogeneous groups of people is preferred in the methods according tothe invention described hereinbelow, with a homogeneous group beingdefined as a group of individuals with as many comparable properties aspossible, the only difference being the presence or absence of thedisease.

Preferably, a normalized spectrum of metabolites in a body fluid of amammal comprises a set of data coming from a homogeneous group ofindividuals. That means that a difference profile according to theinvention for detection of a disease in a male individual comprises NMRspectral line positions with corresponding signal intensities ofpreferably exclusively male individuals. A difference profile for adisease can therefore be different depending on the properties of theindividuals from which it has been obtained.

Preferably, a normalized spectrum of metabolites in a body fluid of amammal represents a set of data coming from at least two, morepreferably at least three, still more preferably at least four, and evenmore preferably at least five individuals.

A difference profile can very suitably comprise 3 to 1,000 spectral linepositions corresponding to possibly original spectral lines. Preferably,a difference profile according to the invention comprises 10 to 500,more preferably 15 to 100, and still more preferably 20 to 70 spectralline positions. Very good results have been obtained with a differenceprofile comprising 30 to 50 spectral line positions.

The number of spectral line positions from which the difference profileis built up is chiefly determined by the definition of the thresholdvalue mentioned. This threshold value, in which the value for the pitchof the noise in the normalized spectra can have been taken into account,indicates from which value differences in the height of a spectral linebetween individuals in which a disease has been diagnosed and healthyindividuals are “significant”. A difference in height can be eitherpositive (increase of intensity) or negative (decrease of intensity).

As said, the detection of a disease by means of a difference profileaccording to the invention is preferably used in individuals withproperties which are corresponding or similar to those of theindividuals from which the difference profile has been obtained, butthis is by no means necessary.

The present invention also relates to a method for manufacturing adifference profile for the detection of a disease in a mammal.

A difference profile according to the invention can very suitably bemanufactured by means of a method comprising the step of providing afirst set of positions and corresponding intensities of spectral linesin an NMR spectrum which has been recorded from metabolites in a bodyfluid of healthy individuals of a mammal.

As a body fluid which can be used in a method according to theinvention, in principle, any body fluid can be used. Preferably, a bodyfluid is used which can be obtained in a non-invasive manner. It is mostpreferred that the body fluid be urine.

Although, in embodiments of the present invention, in principle,different measurement methods for measuring metabolites in a body fluidcan be used, preferably proton nuclear magnetic resonance spectroscopyis used. An NMR instrument with a frequency of at least approximately200 MHz is, in principle, suitable, but there is a preference for use ofinstruments with a higher frequency, such as at least approximately 300MHz, more preferably at least approximately 400-600 MHz.

For carrying out NMR spectroscopic analysis, samples of a body fluid canvery suitably be lyophilized and the lyoplilisate can then bereconstructed in a suitable buffer, for instance a sodium phosphatebuffer, which is prepared on the basis of D₂O. A suitable acid contentfor such a buffer is in the range of pH 4-10, preferably of pH 4-8, andmore preferably, such a buffer has a pH of approximately 6. Preferably,different samples which will be mutually compared are reconstructed inbuffers of equal pH. The reconstitution of the lyophilized components ofa sample of a body fluid in a buffer of equal pH serves to minimizespectral differences caused by differences in pH between differentsamples. To the reconstructed sample, further, an internal standard,such as for instance TMSP (sodiumtrimethylsilyl-[2,2,3,3,-²H₄]-1-propionate) or tetramethylsilane can beadded. Then, an NMR spectrum can be recorded from these samples, the NMRinstrument being set for ¹H NMR analysis. Preferably, an NMR spectrum ofa sample is recorded in triplicate. In general, default settings asrecommended by the manufacturer can be used for this purpose. Themeasurement results are shown in chemical shift in relation to theinternal standard and are expressed in “ppm” (parts per million).

In the present invention, a spectral line position is expressed in“ppm”, while the signal intensity is expressed in “regression” (see alsoFIG. 2), as is conventional in the field.

To the recorded spectra, optionally, a manual baseline correction isapplied and the spectra are then processed into so-called line listingsby means of standard NMR procedures. For this purpose, all lines in thespectra above the noise are collected and converted into a data filewhich is suitable for multivariate data analysis.

Preferably, several healthy individuals of the respective mammal aremeasured so that glitches can be arithmetically taken into account. Suchan arithmetic account of glitches can very suitably take place incombination with the process of normalization of the measurement data.For determining a normalized spectrum of metabolites in a body fluid ofa healthy mammal, in principle, one single healthy individual can bemeasured, but preferably, spectra coming from a group of healthyindividuals are used, more preferably a homogeneous group.

Normalization of several recorded NMR spectra contributes to thereliability of a set of values obtained from a plurality of individuals.Further, normalization allows the comparison of a separately recordedspectrum with a set of previously recorded spectra.

A method for manufacturing a difference profile also comprises the stepof providing a second set of positions and corresponding signalintensities of spectral lines in an NMR spectrum which has been recordedin a corresponding manner from metabolites in a corresponding body fluidof individuals of that same mammal in which the specific disease hasbeen diagnosed.

Preferably, here as well, several individuals of a homogeneous group ofthe respective mammal in which the respective disease has been diagnosedare measured so that glitches can be arithmetically taken into account.To the recorded spectra, optionally, a manual baseline correction isapplied and the spectra are then processed into so-called line listingsby means of standard NMR procedures. For this purpose, all lines in thespectra above the noise are collected and converted into a data filewhich is suitable for multivariate data analysis. The recorded NMRspectra are preferably normalized in the above-described manner.

Finally, a method for manufacturing a difference profile comprises thestep of comparing the normalized spectral line intensities correspondingto corresponding spectral line positions in the first and second set ofpositions of spectral lines in an NMR spectrum, and detecting thedifferences between them for obtaining a difference profile according tothe invention.

Multivariate data analysis or pattern recognition can very suitably beused to visualize differences related to disease and treatment in thesespectra. The arithmetic method based on the Partial-Linear-Fit algorithmas described in WO 02/13228 is particularly preferred. This algorithmenables adjustment of small variations in the position of the spectralline in NMR spectra without loss of resolution.

The above-described Partial-Linear-Fit algorithm comprises a principalcomponent discriminant analysis (PCDA) part. Here, the number ofvariables is first reduced by means of principal component analysis(PCA). The projections, so-called scores, of samples on the firstprincipal components (PCs) are used as a starting point for lineardiscriminant analysis. The scores of the samples are plotted in a scoreplot, where similar samples tend to cluster and dissimilar samples willbe spaced a larger distance from each other (see FIG. 1). The relationof discriminant axes to the original variables (NMR signals) isvisualized in a loading plot. Here, the position of the originalvariables is shown so that the length of the variable vector parallel toa discriminant is proportional to the loading of that variable to thataxis.

Another possibility to visualize the data is by means of factor spectra(see inter alia FIG. 2), which correlate to the positions of clusters inscore plots (e.g. the osteoarthritis cluster in FIG. 1) by graphicalrotation of loading vectors. These factor spectra, or metabolicfingerprints, made in the direction of maximum separation of onecategory in relation to another category, provide insight in the typesof metabolites responsible for separation between the categories.

Therefore, a difference profile according to the present invention canvery suitably be shown as a factor spectrum, an example of which isshown in FIG. 2, or as a table with spectral line positions, an exampleof which is shown in Table 1 below. TABLE 1 Characteristic increasingand decreasing NMR spectral line positions due to osteoarthritis NMRspectral line positions with NMR spectral line positions with increasingvalues due to decreasing values due to osteoarthritis in ppm ±0.05osteoarthritis in ppm ±0.05 1.35 0.93 1.65 1.20 2.00 1.33 2.17 1.45 2.231.48 2.42 1.90 2.45 2.75 2.48 3.20 2.50 4.13 2.58 6.63 2.80 7.30 2.888.32 2.90 3.02 3.08 3.10 3.30 3.50 3.65 4.03 4.33 5.97 6.42 6.45 6.78

Since, in the present invention, the analytical methodology of protonnuclear magnetic resonance spectroscopy is used for obtaining numericdata concerning metabolites, the values obtained depend on the settingsof the instrument and the conditions under which the measurement iscarried out. Also, the absolute values depend on the reference (e.g. theinternal standard) used in the measurement. A difference profile,examples of which are shown in Table 1, thus comprises values which candiffer between different measurement moments and between differentmeasurement conditions. For this reason, the values as shown in Table 1are not absolute values. The meaning of the individual values of boththe spectral line positions and the possible spectral line intensitiesin the difference profile for osteoarthritis thus substantially residesin their ratio and position in relation to each other and therefore inthe pattern of these values.

Due to deviant measurement conditions as indicated hereinabove, the ppmvalue of a spectral line defined in Table 1 can be located at a pointwith a ppm value of ±0.05 ppm as shown in Table 1.

The present invention further relates to a method for the detection of adisease in a mammal, comprising the steps of providing an NMR spectrumof metabolites in a body fluid of an individual of this mammal in whicha particular disease is suspected and comparing this NMR spectrum withone or more difference profiles for particular diseases determinedaccording to the invention for a corresponding body fluid in acorresponding mammal. Such a comparison step can be carried outvisually, but also arithmetically.

Diseases which can be detected by means of the present invention are,for instance, immunological diseases and (chronic) inflammatorydiseases, degenerative processes (and of course also regenerativerecovery processes), cancer, and/or systemic diseases such as systemiclupus erythematosus (SLE), rheumatoid arthritis (RA) or systemicsclerosis. A non-exhaustive list of diseases which can be diagnosed andprognosticated using the present invention is shown in Table 2. TABLE 2Diseases which can be diagnosed and prognosticated by means of thepresent invention. Immunological diseases, Systemic diseases and(chronic) Inflammatory diseases Active chronic hepatitis AllergiesAngioneurotic edema Anti-phospholipid syndrome Anti-phospholipidsyndrome Temporal arteritis Ataxia Telangiectasia Autoimmune gastritisAutoimmune hemolytic anemia Autoimmune hepatitis C1-esterase deficiencyChediak Higashi Syndrome Chronic granulomatous disease (CGD) Chronicfatigue syndrome (CFS, ME) Chronic mucocutaneous candidiasis Chronicsinusitis Ulcerative colitis Complement deficiency CREST syndromeCryoglobulinemia CVID (Common variable immunodeficiency) DermatomyositisDiabetes mellitus type I Discoid lupus erythematosus Febris e.c.i.(feverof unknown origin) Sex-linked agammaglobulinemia (XLA) HomocystinuriaHypereosinophilic syndrome Hyper IgM Hyper-IgD syndrome Hyper-IgEsyndrome Hypersensitivity vasculitis Hypogammaglobulinemia Idiopathicthrombocytopenic purpura IgA- deficiency IgG subclass deficiencyImmunodeficiency with thymoma Infections of unknown origin Interstitialcystitis Keratoconjunctivitis sicca Leukopenia of unknown originLeukocyte adhesion deficiency Disseminated lupus erythematosusLupus-like syndrome Microscopic polyangiitis (MPA) Mixed connectivetissue disease (MCTD) Multiple sclerosis Myasthenia gravisMyeloperoxidase (MPO) deficiency Pemphigus Pernicious anemiaPolyangiitis overlap syndrome Polyarteritis nodosa (PAN) Polymyalgiarheumatica Polymyositis Primary myxedema Primary biliary cirrhosisPrimary neutropenia Progressive systemic sclerosis Relapsingpolychondritis Rheumatoid arthritis Giant cell arteritis Sarcoidosis(Besnier-Boeck disease) SCID (Severe Combined Immunodeficiency)Scleroderma polymyositis Scleroderma Subacute cutaneous lupuserythematosus Ehlers-Danlos Syndrome Goodpasture Syndrome Marfan'sSyndrome Sjogren's Syndrome Stickler Syndrome Systemic lupuserythematosus (SLE) Uveitis Vasculitis Wiskott-Aldrich syndromeWiskott-Aldrich syndrome X-linked agammaglobulinemia X-linkedlymphoproliferative syndrome Addison's disease Behcet's diseaseChurg-Strauss syndrome Crohn's disease Ophthalmic Graves' diseaseHashimoto's disease Reiter's disease Takayasu arteritis Tietze's diseaseWegener's disease Cancer Pancreas cancer Cervical cancer Uterine cancerBladder cancer Bone marrow cancer Breast cancer Intestinal cancer Coloncancer Skin cancer Throat cancer Leukemia Liver cancer Lung cancerStomach cancer Kidney cancer Pancreas cancer Prostate cancer Thyroidcancer Testicular cancer Hodgkin's disease Kahler's disease Infectiousdiseases Bovine brucellosis Blue ear disease Actinomycosis Rheumaticfever African horse sickness African swine fever AIDS Equineencephalomyelitis Anaplasma infection Atrophic rhinitis Bacillarhemoglobinemia Contagious agalactia Contagious bovine pleuropneumoniaContagious epididymitis Contagious lymphatic vessel inflammationContagious equine metritis Contagious pleuropneumonia Pig typhoidEchinoccosis Hydatidosis Purpura hemorrhagica Bovine malignant catarrhShipping fever Botulism Bovine Spongiforme Encephalopathy (BSE) Bovinevirus diarrhea (BVD) Bronchitis Bronchopneumonia Typhoid Chlamydophilaabortus Cholera Coccidiosis Conjunctivitis Coxsackie virus infectionCryptosporidiosis Cysticercosis Cytomegalia Intestinal infectionDermatophilosis Diphtheria Dourine Dysentery Encephalitis Enzooticbovine leukosis Enterocolitis Enterotoxemia Erythema infectiosum Typhoidfever Gas gangrene Gastritis Giardiasis Gingivitis Influenza HeartwaterHepatitis Herpes Herpes zoster HIV infection Rabies HPV infectionInfectious anemia Neonatal septicemia of sucklings KeratoconjunctivitisClassical swine fever Classical fowl plague Infectious bovinerhinotracheitis Legionella pneumonia Leptospirosis Liver flukeLasteriosis Longadenomatosis Pneumonia Lyme disease Malaria Malta fever(brucellosis) Mastitis Meningitis Meningoencephalitis Metritis AnthraxFoot-and-mouth disease Epidemic myalgia Myositis Myxomatosis Nairobisheep disease Necrobacillosis Nodular dermatosis Equine influenzaParadontitis Parasitic diseases Paratuberculosis infection Paratyphoidfever Peritonitis Piroplasmosis Pleuropneumonia Pododermatitis SmallpoxPoliomyelitis Polyarthritis Polyserositis Pseudo foot-and-mouth diseasePseudo membranous enteritis Pseudo tuberculosis Newcastle disease Pulpynephritis Q-fever Rhinitis Rhinopneumonia Rift Valley fever RinderpestFungous infections Scrapie Neonatal septicemia Sexually transmitteddiseases Streptococci group A-infections Streptococci group B-infectionsSubacute bacterial endocarditis Teschen disease Tetanos TetanusTheileriosis Toxic shock syndrome Toxoplasmosis TrichinellosisTrichinosis Trichomonas infection Trypanosomiasis Tuberculosis TularemiaVesiculitis Viral hemorrhagic disease Viral myocarditis Spotted feverSwine erysipelas Erysipelas Bornholm disease Carré's diseaseCreutzfeldt-Jakob disease Glässer's disease Mucocutaneous lymph nodesyndrome Glandular fever Tyzzer's disease Weil's disease ZoonosesMaedi-Visna Degenerative diseases Amyotrophic lateral sclerosis(Charcot's disease) Atherosclerosis Chromosome 17-linked dementiaCorticobasal degeneration Cystic Fibiosis/Mucoviscidosis Diffuse Lewybody diseases Discopathy Frontotemporal dementia Lewy body dementiaOsteoarthritis Osteomyelitis Osteoporosis Primary progressive aphasiaProgressive supranuclear palsy (PSP) Progressive muscular dystrophy(Duchenne muscular dystrophy) Spondylarthrosis Vascular dementiaAlzheimer's disease Binswanger's disease Creutzfeldt-Jakob diseaseGaucher's disease Huntington's disease Korsakoff's disease Parkinson'sdisease Pick's disease Pompe's disease

It is possible, but not necessary, to normalize the NMR spectrum ofmetabolites in a body fluid of an individual of this mammal in which thedisease is suspected prior to comparing it with a difference profileaccording to the invention by means of spectra of metabolites in a bodyfluid of healthy individuals of the respective mammal. If it appearsfrom the comparison step that the characteristic difference profile isreally comprised in the spectrum recorded from an individual in whichthe disease is suspected, the presence of the disease is thusdetermined.

It is also possible to plot the data of the spectrum recorded from anindividual in which the disease is suspected in a score plot, such asfor instance the score plot of FIG. 1, and to determine whether the datafall within the cluster of “ill” spectra. If these data of an individualin which the respective disease is suspected do not fall within thecluster designated “ill”, the respective disease is not present in therespective individual, at least not at the disease stage as it occurredin the “ill” reference group. In the present invention, such adiagnostic method step is understood to be comprised in the step forcomparing an NMR spectrum with a difference profile.

Metabolites are conversion products of organic compounds which are foundin the body in different forms and numbers. For instance, in a healthybody, the ratio and the occurrence of metabolites in a body fluid, suchas urine or blood, are totally different than in an unhealthy body. Inurine, such metabolites are considered waste products.

In the present context, biomarkers are understood to mean one or moreorganic compounds or their metabolites, or specific patterns or specificamounts of several organic compounds or their metabolites, which can befound in the body of a mammal and which are the result of a subclinicalor clinical event in that body.

By measuring biomarkers in a body fluid of a mammal, it is possible toquickly distinguish an unhealthy or ill condition from a healthycondition. The present invention provides a method for theidentification of biomarkers.

A biomarker according to the invention can be one single substance ormetabolite, but also a specific combination of substances ormetabolites. In the latter case, it can also be considered a set ofbiomarkers. Preferably, according to the present invention, a biomarkeris a specific combination of metabolites which, as a result of thedisease, can be found in a specific pattern of concentrations or amountsin a body fluid, preferably urine, and which can be derived from adifference profile. In the present invention, a biomarker is alsounderstood to mean moieties of organic compounds or of metabolites.

The present invention provides a method for the identification of abiomarker for a particular disease, comprising manufacturing adifference profile for that specific disease according to the inventionand identifying one or more metabolites characterized by one or moredefined spectral lines in this difference profile.

The identification of a metabolite which is characterized by one or moredefined spectral lines in a difference profile can, for instance, bedone by the coupling of a mass spectrometer to an NMR instrument and thesubsequent analysis of the metabolite corresponding to one or moredefined spectral lines by means of mass spectrometry (MS). A skilledperson is familiar with mass spectrometry for the identification oforganic compounds and metabolites. However, determining the identity ofa metabolite corresponding to one or more defined spectral lines canalso be done by recording the NMR spectrum from known metabolites andcomparing it to the NMR spectral lines in a difference profile accordingto the invention.

For identifying the metabolites corresponding to the different spectralline positions, for instance, also the handbooks such as “SadtlerStandard Spectra series on NMR spectra” and “Aldrich Library of NMRSpectra” or other database files for ¹H NMR spectra can be consulted.

The ¹H chemical shifts of particular characteristic metabolites are, forinstance (values ±0.05 ppm): N-acetylaspartate (CH3) appears as asinglet at 2.05 ppm (designation CH3), and as a multiplet at 2.91 and1.95 ppm (designation CH2); inositol appears as a doublet at 3.25 ppm(designation H1/H3) and as a triplet at 4.10 ppm (designation H2);choline appears as a multiplet at 3.19 ppm (designation NCH2) and as amultiplet at 3.94 ppm (designation OCH2); neopterin appears as amultiplet at 4.34 and 4.44 ppm and (designation CH2), as a multiplet at4.60 and 4.70 ppm (designation CH), and as a singlet at 5.20 ppm(designation OCH2), and taurine appears as a triplet at 3.26 ppm(designation CH2SO3) and 3.31 ppm (designation NCH2). Such metabolitescan very suitably be used as biomarkers according to the presentinvention for detecting a disease in a patient, where increases in theconcentration of the biomarkers indicate, for instance, the (increased)degradation or conversion of the base material from which thesemetabolites originate.

It could be determined that a difference profile according to theinvention, a representative example of which is shown in Table 1 andFIG. 2, contains a different pattern of spectral lines with a positiveregression. (i.e. spectral lines whose height has increased) andspectral lines with a negative regression (i.e. spectral lines whoseheight has decreased) for individual diseases, which spectral lines arecharacteristic of specific metabolites.

For instance, it could be determined that the spectral lines which showan increase in intensity in FIG. 2 (factor spectrum for osteoarthritis)are specific for lactic acid, malic acid, mercapturic acid and/or acetylcysteine and monophosphates.

It is assumed that these metabolites are secreted in the urine as aresult of the disease, and the accompanying complex physiologicaldegradation and inflammatory symptoms, and that thus, the secretion ofthese metabolites in the urine is specific for the presence of thedisease.

Metabolites that are found in increased amounts in a body fluid, e.g.the urine, of patients which are examined for the presence of a diseasecan very suitably be used as a biomarker. Metabolites which decrease inamount in ill individuals in relation to healthy individuals can lesswell be applied as a biomarker due to the danger of false negativeresults in particular detection methods. Metabolites with a positiveregression in a difference profile according to the invention aretherefore preferably used as a biomarker in a system for the rapid andearly detection of a disease.

In many cases, it will not be possible to conclude from the differenceprofile whether the metabolites are secreted in the urine in freecondition or in a derived form, for instance conjugated or bound inanother manner. However, a skilled person will understand that themetabolites described can be used as a biomarker in any condition inwhich they may be found in the body fluid.

The invention also relates to biomarkers for diagnosis and prognosis ofosteoarthritis, available by using a method according to the invention.In particular, the present invention provides a biomarker forosteoarthritis characterized in that this biomarker is formed by ametabolite containing at least one compound, which metabolite is chosenfrom the group consisting of lactic acid, malic acid, mercapturic acid,acetyl cysteine, monophosphate compounds and their functional analogs.

The present invention further relates to a method for the detection(i.e. the diagnosis and/or prognosis) of a disease in a mammal,comprising measuring a biomarker according to the invention in a bodyfluid, preferably urine. Such a measurement is preferably non-invasive,and preferably comprises the detection, in a body fluid of an individualof a mammal in which a disease is suspected, of a quantitative change inthe occurrence of a biomarker in relation to a normal value for thatbiomarker which is found in a body fluid of healthy individuals andwhich quantitative change corresponds to the regression of thatbiomarker in the difference profile for the respective disease.

A measurement of a biomarker can also comprise the detection of apattern of concentrations or amounts of metabolites in a body fluid ofan individual of a mammal in which a disease is suspected in the casethat the biomarker is a pattern of several metabolite concentrations. Ifsuch a pattern of concentrations or amounts of metabolites, whichpattern is measured in the form of a biomarker measurement in anindividual of a mammal, corresponds to the difference profile of therespective disease for which the biomarker has been determined, thedisease is present in that individual. In that case, a qualitativebiomarker measurement is involved.

So, a method for detection of a disease in a mammal according to theinvention comprises the quantitative or qualitative detection of abiomarker according to the invention in a body fluid of that individual.

A measurement of a biomarker for detection of a disease in a mammalaccording to the invention is preferably carried out for urine.

A measurement of a biomarker in a body fluid of an individual of amammal for the detection of a disease according to the invention willalways comprise the step of comparing the measurement value found to areference, which reference can comprise a characteristic value forhealthy individuals and/or a characteristic value for individuals inwhich the respective disease has been diagnosed.

A diagnose can be made on the basis of the results of the measurement ofa biomarker according to the invention. For instance, a normal level ofmetabolites or a normal pattern of metabolites will provide thediagnosis “healthy”. Conversely, an undesired metabolite pattern or anundesired metabolite level will provide the diagnosis “ill”, where,depending on the specificity and nature of the disease-specific markerused, the name of the disease is known.

By means of the present invention, it is therefore possible to detect adisease in a mammal by observing specific biochemical changes in thebody fluid of an individual of a mammal, which changes are preferablydetected by measurement of a biomarker according to the invention.

A biomarker according to the invention can be measured in a body fluidin different manners. For instance, NMR and/or Mass Spectrometry (MS)can be applied to a sample of a body fluid. But other analytical methodscan also be used for this purpose, such as ELISA or a relatedmethodology.

An even simpler and more rapid diagnosis can be made by usingmicrosystem technologies, for instance by using a “microfluidics”instrument or a microelectromechanic system (MEMS) in combination with,for instance, specific fluorescent enzymes or other manners of detectionby means of which the biomarkers found in a body fluid can bequantitatively and/or qualitatively measured. A skilled person will beable, without many problems, to acquaint himself with the state of theart in the area of the rapid detection of biomarkers and/or metabolitesand is able to formulate methods for measuring biomarkers according tothe present invention in a body fluid of a mammal for the diagnosis orprognosis of a disease. (See for instance M. Madou, Fundamentals ofMicrofabrication: The Science of Miniaturization, 2^(nd) Ed, CRC Press1997; N. Nam-Trung & S. Wereley, 2002, Fundamentals and Applications ofMicrofluidics, Artech House Publishers; J. W. Gardner et al., 2001,Microsensors, MEMS and Smart Devices, Wiley, Chichester).

The present invention also relates to an apparatus for using a methodfor the detection of a disease in a mammal by measuring a biomarkeraccording to the invention. Such an apparatus preferably comprises asolid carrier with immobilized binding partners for this biomarkerthereon. The nature of such binding partners depends on the biomarkerwhich will be measured, but can, for instance, comprise an antibody or apeptide as a specific binding partner which is able to specifically bindthe biomarker. An apparatus according to the invention furtherpreferably comprises a system for quantitative detection of bindingbetween the biomarker and the immobilized binding partners. Such asystem can comprise either direct detection (for instance by applyingfluorescent labels on the biomarker) or indirect detection (for instanceby applying a secondary binding partner to the biomarker, whichsecondary binding partner comprises a detectable label). A skilledperson is assumed to be familiar with systems and methods for bringingabout a bond between an immobilized binding partner and a biomarkeraccording to the invention and the systems for detecting the bondbetween them.

By means of the present systems and methods, a disease can be diagnosedin a qualitative manner. For this purpose, for instance, a database iscompiled of NMR spectra recorded from substantially all metabolites in abody fluid, preferably urine, of one or more individuals with a defineddisease, such as one or more NMR spectra of, for instance,osteoarthritis patients and/or one or NMR spectra of patients sufferingfrom a disease according to Table 2, for instance multiple sclerosispatients. The known NMR spectra of such a database can be compared to anNMR spectrum recorded from a patient in which a particular disease, forinstance osteoarthritis, is suspected. If such a database only comprisesone or more NMR spectra of patients suffering from osteoarthritis, onlyqualitative detection of osteoarthritis is possible by means of such adatabase. If, however, the database contains NMR spectra of a largenumber of different and defined diseases, in a patient in which adisease is suspected, the qualitative detection of a large number ofdiseases will be possible. It will be possible to carry out thisdetection by comparison of an NMR spectrum of this patient sufferingfrom an unknown disease with the NMR spectra in the database. If such acomparison step yields a match with NMR spectra in the database for aspecific disease, the disease is thus demonstrated in this respectivepatient. A database base comprises such NMR spectra preferably innormalized form.

In addition to the fact that a database according to the invention cancomprise one ore more optionally normalized NMR spectra for one or moredefined diseases, such a database can instead comprise one or moredifference profiles according to the invention, formulated for one ormore defined diseases.

The use of difference profiles in a database according to the inventionhas the advantage that the database will comprise considerably fewerdata than in the case in which complete, optionally normalized, NMRspectra are stored in it.

By formulating difference profiles for one or more diseases at differentstages of progression and including them in a database, a quantitativeseries of difference profiles for quantitative analysis of a disease canbe obtained. By carrying out a comparative analysis of an NMR spectrumof an individual in which a particular disease is suspected, or of whichthe severity of the disease is to be determined, this quantitativeseries of difference profiles can be used to quantitatively express thepresence of a disease. Further, the progression of the disease can bequantitatively followed in this manner.

Therefore, the present invention also relates to database comprising oneor more disease-specific difference profiles according to the invention,optionally with annotation of the stage of the disease.

Preferably, such a database comprises difference profiles for diseaseswhich are difficult to diagnose or difficult to prognosticate. Verysuitably, a database according to the invention comprises differenceprofiles for different types of cancer, leukemia, Parkinson's disease,Hodgkin's disease, Crohn's disease, Alzheimer's disease, AIDS, diabetes,tuberculosis, multiple sclerosis, amyotrophic lateral sclerosis,cerebrospinal meningitis, poliomyelitis, progressive muscular dystrophy,encephalitis, tetanus, viral hepatitis, malaria, spotted fever, typhoidfever, paratyphoid fever, diphtheria, cholera, anthrax, osteoarthritis,osteoporosis, allergies and/or mucoviscidosis.

It is also possible to use a biomarker according to the invention forquantitative analysis of a disease if the quantity in which thisbiomarker is found in a body fluid of ill individuals can be correlatedto different stages of progression of the respective disease.

By using the present invention in combination with metabolic andphysiological measurements, it is now, for instance, possible todiagnose and quantify osteoarthritis at an early stage. This analysis ofosteoarthritis, the knowledge of the pathogenesis and the efficiency oftherapies can greatly improve through use of the present invention. Byusing a biomarker according to the invention, such as a biomarker chosenfrom the group consisting of lactate, malate, β-alanine, hypoxanthine,3,4-dihydroxy mandelate, 3-hydroxy cinnamic acid, alanine, aspargine orN-acetyl aspartate, alone, or in combination, it is thus now possible todetect osteoarthritis at an early stage and to improve the treatment ofpatients.

In principle, the invention can be applied to animals, including fishes,birds, and is preferably applied to mammals in general and to equines,bovines, porcines, ovines, myomorpha, canines, rodentia, simians andprimates in particular. Preferably, the invention is applied to guineapigs, dogs or humans.

The invention will be illustrated hereinbelow on the basis of anexample.

EXAMPLE 1

Sample Preprocessing

Prior to NMR spectroscopic analysis, 1 ml urine samples were lyophilizedand reconstructed in 1 ml of sodium phosphate buffer (pH 6.0, based onD₂O) with 1 mM of sodium trimethylsilyl-[2,2,3,3,2H4]-1-propionate(TMSP) as an internal standard.

NMR Measurements

NMR spectra were recorded in triplicate in a fully automated manner on aVarian UNITY 400 MHz spectrometer provided with a proton NMR set-up andat a working temperature of 293 K. Free induction decays (FIDs) werecollected as 64K data points with a spectral band width of 8,000 Hz;45-degree pulses were used with a measurement time of 4.10 sec. and arelaxation delay of 2 sec. The spectra were determined by accumulationof 128 FIDs. The signal of the residual water was removed by apresaturation technique in which the water peak was irradiated with aconstant frequency for 2 sec. prior to the measurement pulse.

The spectra were processed using the standard Varian software. Anexponential window function with a line broadening of 0.5 Hz and amanual baseline correction was applied to all spectra.

After reference to the internal NMR standard (TMSP δ=0.0), line listingswere compiled by means of the standard Varian NMR software. To obtainthese line listings, all lines in the spectra with a signal intensityabove the noise were collected and converted to a data file which wassuitable for use of multivariate data analysis.

Determination of Metabolic Fingerprint or Difference Profile ofOsteoarthritis Metabolites.

By means of a 400 MHz NMR spectrometer, urine samples were tested ofhealthy individuals and of individuals in which osteoarthritis had beendiagnosed. The spectra were processed and line listings were compiled bymeans of standard Varian software after reference to the internalstandard. The NMR data reduction file was imported into Winlin VI. 10.Small variations of comparable signals in different NMR spectra wereadjusted by using the Partial-Linear-Fit algorithm as described in WO02/13228 and the lines were fitted without loss in resolution. The scaleof the data was automatically adjusted and “normalized” to unitintensity. The endogenous and exogenous metabolites were eliminated fromthe NMR spectra, which led to the reduction of the data to specific and“significant” osteoarthritis-related changes. For this purpose, athreshold value was used by means of which 80-90% of the spectral linepositions were eliminated.

A score plot (FIG. 1) of the NMR spectra was made by means ofmultivariate data analysis as described hereinabove. From the scoreplot, a metabolic fingerprint or difference profile was obtained byselecting rising and falling NMR signals with relatively high frequencyof occurrence in urine of osteoarthritis patients. From these, a choicewas made of approximately 35 NMR signals with a relevant contribution toosteoarthritis (regression >0.5). These NMR signals are shown in Table 1and FIG. 2.

1. A difference profile for the detection of a disease in a mammal,comprising a plurality of spectral line positions and optionallycorresponding signal intensities of NMR spectral lines, which expressthe normalized difference between one or more NMR spectra of metabolitesin a body fluid of one or more healthy individuals of said mammal, andone or more corresponding NMR spectra of metabolites in a correspondingbody fluid of one or more individuals of said mammal in which saiddisease has been diagnosed.
 2. A difference profile according to claim1, wherein said mammal has been chosen from the group consisting ofprimates, dogs and rodents.
 3. A difference profile according to claim1, wherein said body fluid is urine.
 4. A difference profile accordingto claim 1, wherein said disease is selected from the group consistingof an immunological disease, a (chronic) inflammatory disease, adegenerative disease, cancer, an infectious disease, a systemic disease.5. A difference profile according to claim 1, wherein said disease isosteoarthritis.
 6. A difference profile according to claim 5, comprisingthe spectral lines and values corresponding thereto according toTable
 1. 7. A database comprising one or more difference profilesaccording to claim
 1. 8. A database according to claim 7, wherein saidmammal is a human.
 9. A method for the detection of a disease in amammal, comprising the steps of providing an NMR spectrum of metabolitesin a body fluid of an individual of said mammal in which said disease issuspected and comparing said NMR spectrum with a difference profile froma database according to claim 7, which difference profile has beendetermined for a corresponding body fluid from a corresponding mammal.10. A method according to claim 9, wherein said mammal has been chosenfrom the group consisting of primates, dogs and rodents.
 11. A methodaccording to claim 9, wherein said body fluid is urine.
 12. A methodaccording to claim 9, wherein said disease is osteoarthritis.
 13. Amethod for manufacturing a difference profile for the detection of adisease in a mammal, comprising the steps of: a) providing a firstnormalized set of positions and corresponding signal intensities ofspectral lines of one or more NMR spectra recorded from metabolites in abody fluid of one or more healthy individuals of said mammal; b)providing a second normalized set of positions and corresponding signalintensities of spectral lines of one or more NMR spectra recorded frommetabolites in a corresponding body fluid of one or more individuals ofsaid mammal in which said disease has been diagnosed; and c) detectingthe spectral lines whose signal intensities differ between said firstand second set, for obtaining said difference profile.
 14. (canceled)15. A method according to claim 13, wherein said disease isosteoarthritis.
 16. A method for identifying a biomarker for a disease,comprising manufacturing a difference profile according to claim 1 andidentifying one or more metabolites which are characterized by one ormore defined spectral lines in said difference profile, which one ormore metabolites, alone or in combination, characterize said biomarker.17. A method according to claim 16, wherein said one or more metabolitesare characterized by one or more defined spectral lines with a positiveregression.
 18. A method according to claim 16, wherein said disease isosteoarthritis.
 19. A biomarker for the detection of a disease in amammal, comprising one or more metabolites or parts thereof which arecharacterized by one or more defined spectral lines in a differenceprofile according to claim
 1. 20. A biomarker for the detection ofosteoarthritis, comprising one or more metabolites or parts thereofchosen from the group consisting of lactate, malate, β-alanine,hypoxanthine, 3,4-dihydroxy mandelate, 3-hydroxy cinnamic acid, alanine,aspargine and N-acetyl aspartate, and combinations thereof.
 21. Use of abiomarker according to claim 19, for the detection of a disease in amammal.
 22. Use of a biomarker according to claim 20, for the detectionof osteoarthritis in a mammal.
 23. A method for detection of a diseasein a mammal, comprising measuring a biomarker according to claim 19, ina body fluid of an individual of said mammal.
 24. A method according toclaim 23, wherein said body fluid is urine.
 25. An apparatus for use ofa method according to claim 23, comprising a solid carrier with one ormore immobilized binding partners for said biomarker thereon.
 26. Anapparatus according to claim 25, further comprising a system for thequantitative detection of binding between said biomarker and said one ormore immobilized binding partners.
 27. A database comprising one or moredifference profiles according to claim
 4. 28. A database comprising oneor more difference profiles according to claim
 6. 29. A databaseaccording to claim 27, wherein said mammal is a human.
 30. A databaseaccording to claim 28, wherein said mammal is a human.
 31. A method forthe detection of a disease in a mammal, comprising the steps ofproviding an NMR spectrum of metabolites in a body fluid of anindividual of said mammal in which said disease is suspected andcomparing said NMR spectrum with a difference profile from a databaseaccording to claim 8, which difference profile has been determined for acorresponding body fluid from a corresponding mammal.
 32. A methodaccording to claim 31, wherein said disease is osteoarthritis.
 33. Amethod for identifying a biomarker for a disease, comprisingmanufacturing a difference profile according to claim 6 and identifyingone or more metabolites which are characterized by one or more definedspectral lines in said difference profile, which one or moremetabolites, alone or in combination, characterize said biomarker.
 34. Abiomarker for the detection of a disease in a mammal, comprising one ormore metabolites or parts thereof which are characterized by one or moredefined spectral lines in a difference profile according to claim
 6. 35.A method for detection of a disease in a mammal, comprising measuring abiomarker according to claim 20 in a body fluid of an individual of saidmammal.
 36. An apparatus for use of a method according to claim 24,comprising a solid carrier with one or more immobilized binding partnersfor said biomarker thereon.
 37. An apparatus according to claim 36,further comprising a system for the quantitative detection of bindingbetween said biomarker and said one or more immobilized bindingpartners.